text stringlengths 1 93.6k |
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param_group['lr'] = learning_rate
|
val_loss_old = val_loss # Update old validation loss
|
if epoch % test_every == 0 or epoch == max_epochs-1:
|
# Test
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test_time, test_loss, test_err_edges, test_err_tour, test_err_tsp, test_pred_tour_len, test_gt_tour_len = test(net, config, epoch_bar, mode='test')
|
epoch_bar.write('T: ' + metrics_to_str(epoch, test_time, learning_rate, test_loss, test_err_edges, test_err_tour, test_err_tsp, test_pred_tour_len, test_gt_tour_len))
|
writer.add_scalar('loss/test_loss', test_loss, epoch)
|
writer.add_scalar('pred_tour_len/test_pred_tour_len', test_pred_tour_len, epoch)
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writer.add_scalar('optimality_gap/test_opt_gap', test_pred_tour_len/test_gt_tour_len - 1, epoch)
|
# Save training checkpoint at the end of epoch
|
torch.save({
|
'epoch': epoch,
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'model_state_dict': net.state_dict(),
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'optimizer_state_dict': optimizer.state_dict(),
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'train_loss': train_loss,
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'val_loss': val_loss,
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}, log_dir+"last_train_checkpoint.tar")
|
# Save checkpoint after every 250 epochs
|
if epoch != 0 and (epoch % 250 == 0 or epoch == max_epochs-1):
|
torch.save({
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'epoch': epoch,
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'model_state_dict': net.state_dict(),
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'optimizer_state_dict': optimizer.state_dict(),
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'train_loss': train_loss,
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'val_loss': val_loss,
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}, log_dir+f"checkpoint_epoch{epoch}.tar")
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return net
|
if __name__ == "__main__":
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main(config)
|
# <FILESEP>
|
from enum import Enum
|
from fastapi import Request, FastAPI, HTTPException
|
from fastapi.middleware.cors import CORSMiddleware
|
import os
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import aiohttp
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import json
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from modal import Image, Mount, Secret, Stub, asgi_app
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from utils import pretty_log
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image = Image.debian_slim(python_version="3.10").pip_install("pynacl", "requests")
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discord_secrets = [Secret.from_name("discord-secret-fsdl")]
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stub = Stub(
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"askfsdl-discord",
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image=image,
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secrets=discord_secrets,
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mounts=[Mount.from_local_python_packages("utils")],
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)
|
class DiscordInteractionType(Enum):
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PING = 1 # hello from Discord
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APPLICATION_COMMAND = 2 # an actual command
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class DiscordResponseType(Enum):
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PONG = 1 # hello back
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DEFERRED_CHANNEL_MESSAGE_WITH_SOURCE = 5 # we'll send a message later
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class DiscordApplicationCommandOptionType(Enum):
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STRING = 3 # with language models, strings are all you need
|
@stub.function(
|
# keep one instance warm to reduce latency, consuming ~0.2 GB while idle
|
# this costs ~$3/month at current prices, so well within $10/month free tier credit
|
keep_warm=1,
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)
|
@asgi_app(label="askfsdl-discord-bot")
|
def app() -> FastAPI:
|
app = FastAPI()
|
app.add_middleware(
|
CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
|
allow_methods=["*"],
|
allow_headers=["*"],
|
)
|
@app.post("/")
|
async def handle_request(request: Request):
|
"Verify incoming requests and if they're a valid command spawn a response."
|
# while loading the body, check that it's a valid request from Discord
|
body = await verify(request)
|
data = json.loads(body.decode())
|
if data.get("type") == DiscordInteractionType.PING.value:
|
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